{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/stammler/dustpy/HEAD?labpath=examples%2F2_simple_customization.ipynb)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2. Simple Customization\n",
    "\n",
    "If you do not want to run the standard simulation you can easily modify the initial conditions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-30T11:25:18.284859Z",
     "iopub.status.busy": "2023-11-30T11:25:18.284230Z",
     "iopub.status.idle": "2023-11-30T11:25:19.380758Z",
     "shell.execute_reply": "2023-11-30T11:25:19.379197Z"
    }
   },
   "outputs": [],
   "source": [
    "from dustpy import Simulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-30T11:25:19.387390Z",
     "iopub.status.busy": "2023-11-30T11:25:19.386731Z",
     "iopub.status.idle": "2023-11-30T11:25:19.393680Z",
     "shell.execute_reply": "2023-11-30T11:25:19.392355Z"
    }
   },
   "outputs": [],
   "source": [
    "sim = Simulation()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The simulation object has an attribute to set the initial conditions `Simulation.ini`. The attribute is structured in initial conditions for dust, gas, the grid, and the central star. If you call `Simulatio.initialize()`, the simulation object will be filled according the parameters set here. We'll go through all options one by one.\n",
    "\n",
    "**--> All quantities are in cgs units! <--**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-30T11:25:19.399432Z",
     "iopub.status.busy": "2023-11-30T11:25:19.398785Z",
     "iopub.status.idle": "2023-11-30T11:25:19.413876Z",
     "shell.execute_reply": "2023-11-30T11:25:19.412970Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "namespace(dust=namespace(aIniMax=0.0001,\n",
       "                         allowDriftingParticles=False,\n",
       "                         erosionMassRatio=10.0,\n",
       "                         d2gRatio=0.01,\n",
       "                         distExp=-3.5,\n",
       "                         excavatedMass=1.0,\n",
       "                         fragmentDistribution=-1.8333333333333333,\n",
       "                         rhoMonomer=1.67,\n",
       "                         vfrag=100.0),\n",
       "          gas=namespace(alpha=0.001,\n",
       "                        gamma=1.4,\n",
       "                        Mdisk=9.942049353490256e+31,\n",
       "                        mu=3.847030424486999e-24,\n",
       "                        SigmaExp=-1.0,\n",
       "                        SigmaRc=897587224200000.0),\n",
       "          grid=namespace(Nmbpd=7,\n",
       "                         mmin=1e-12,\n",
       "                         mmax=100000.0,\n",
       "                         Nr=100,\n",
       "                         rmin=14959787070000.0,\n",
       "                         rmax=1.495978707e+16),\n",
       "          star=namespace(M=1.988409870698051e+33, R=139140000000.0, T=5772.0))"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sim.ini"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Stellar parameters\n",
    "\n",
    "The stellar parameters mainly influence the dynamical time scales and the temperature profile."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-30T11:25:19.466125Z",
     "iopub.status.busy": "2023-11-30T11:25:19.465478Z",
     "iopub.status.idle": "2023-11-30T11:25:19.473477Z",
     "shell.execute_reply": "2023-11-30T11:25:19.472384Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "namespace(M=1.988409870698051e+33, R=139140000000.0, T=5772.0)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sim.ini.star"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* M\n",
    "\n",
    "Stellar mass, default: $1\\ M_\\odot$  \n",
    "Has influence on the dynamical timescales in the disk.\n",
    "\n",
    "* R\n",
    "\n",
    "Stellar radius, default: $2\\ R_\\odot$  \n",
    "Has influence on the temperature profile in the disk. The default temperature profile is a passively irradiated disk with a constant irradtion angle of 0.05.\n",
    "\n",
    "* T\n",
    "\n",
    "Effective temperature, default: 5772 K  \n",
    "Has influence on the temperature profile in the disk. The default temperature profile is a passively irradiated disk with a constant irradtion angle of 0.05."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Grid parameters\n",
    "\n",
    "The grid parameters determine the shape of the radial and mass grids. While you can set your own non-standard radial grid (see later), you should under no circumstances meddle with the mass grid, unless you know exactly what you are doing. Please always use the `Simulation.ini.grid` namespace to customize your mass grid. The mass grid has to be strickly logarithmic. Otherwise, the coagulation algorithm will produce wrong results.  \n",
    "**Attentian:** If you changed the mass grid for any reason during the simulation, you have to re-calculate the coagulation parameters in `Simulation.dust.coagulation`.\n",
    "\n",
    "**Note:** The performance of `DustPy` is very sensitive to the mass grid. A finer mass grid slows down the simulation drastically."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-30T11:25:19.477447Z",
     "iopub.status.busy": "2023-11-30T11:25:19.476813Z",
     "iopub.status.idle": "2023-11-30T11:25:19.484568Z",
     "shell.execute_reply": "2023-11-30T11:25:19.483505Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "namespace(Nmbpd=7,\n",
       "          mmin=1e-12,\n",
       "          mmax=100000.0,\n",
       "          Nr=100,\n",
       "          rmin=14959787070000.0,\n",
       "          rmax=1.495978707e+16)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sim.ini.grid"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Nmbpd\n",
    "\n",
    "Number of mass bins per mass decade, default: 7  \n",
    "Should be at least 7, see [Drążkowska et al. (2014)](https://doi.org/10.1051/0004-6361/201423708)  \n",
    "This will have a large impact on the accuracy and the computational costs of the simulation.\n",
    "\n",
    "* mmin\n",
    "\n",
    "Minimum particle mass, default: $10^{-12}$ g\n",
    "\n",
    "* mmax\n",
    "\n",
    "Maximum particle mass, default: $10^{5}$ g\n",
    "\n",
    "* Nr\n",
    "\n",
    "Number of radial grid cells, default: 100\n",
    "\n",
    "* rmin\n",
    "\n",
    "Location of inner radial grid boundary, default 1 AU\n",
    "\n",
    "* rmax\n",
    "\n",
    "Location of outer radial grid boundary, default 1000 AU"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Gas Parameters\n",
    "\n",
    "The gas parameters define the initial conditions of the gas disk. The standard surface density profile is the self-similar solution of [Lynden-Bell & Pringle (1974)](https://doi.org/10.1093/mnras/168.3.603)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-30T11:25:19.488789Z",
     "iopub.status.busy": "2023-11-30T11:25:19.488210Z",
     "iopub.status.idle": "2023-11-30T11:25:19.495532Z",
     "shell.execute_reply": "2023-11-30T11:25:19.494513Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "namespace(alpha=0.001,\n",
       "          gamma=1.4,\n",
       "          Mdisk=9.942049353490256e+31,\n",
       "          mu=3.847030424486999e-24,\n",
       "          SigmaExp=-1.0,\n",
       "          SigmaRc=897587224200000.0)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sim.ini.gas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* alpha\n",
    "\n",
    "alpha viscosity parameter, default: $10^{-3}$  \n",
    "see [Shakura & Sunyaev (1973)](http://adsabs.harvard.edu/abs/1973A%26A....24..337S) for details\n",
    "\n",
    "* gamma\n",
    "\n",
    "heat capacity ratio, default: 7/5\n",
    "\n",
    "* Mdisk\n",
    "\n",
    "Inital gas disk mass, default: $0.05\\ M_\\odot$\n",
    "\n",
    "* mu\n",
    "\n",
    "Mean molecular weight of the gas, default: $2.3\\ m_\\mathrm{proton}$\n",
    "\n",
    "* SigmaExp\n",
    "\n",
    "Power law exponent of surface density profile, default: -1  \n",
    "see [Lynden-Bell & Pringle (1974)](https://doi.org/10.1093/mnras/168.3.603)\n",
    "\n",
    "* SigmaRc\n",
    "\n",
    "Critical cut-off radius of surface density, default: 30 AU  \n",
    "see [Lynden-Bell & Pringle (1974)](https://doi.org/10.1093/mnras/168.3.603)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dust Parameters\n",
    "\n",
    "The dust parameters define the initial conditions of the dust disk and the basic collisional behavior of the dust particles."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-30T11:25:19.500734Z",
     "iopub.status.busy": "2023-11-30T11:25:19.499640Z",
     "iopub.status.idle": "2023-11-30T11:25:19.507705Z",
     "shell.execute_reply": "2023-11-30T11:25:19.506406Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "namespace(aIniMax=0.0001,\n",
       "          allowDriftingParticles=False,\n",
       "          erosionMassRatio=10.0,\n",
       "          d2gRatio=0.01,\n",
       "          distExp=-3.5,\n",
       "          excavatedMass=1.0,\n",
       "          fragmentDistribution=-1.8333333333333333,\n",
       "          rhoMonomer=1.67,\n",
       "          vfrag=100.0)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sim.ini.dust"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* aIniMax\n",
    "\n",
    "Maximum particle size that will be filled initially, default: 1 µm\n",
    "\n",
    "* allowDriftingParticles\n",
    "\n",
    "If `True` initially drifting particles will not be removed, default: `False`  \n",
    "Dust particles in the disk drift inwards more rapidly with increasing Stokes number. In the outer disk the gas surface density is low and therefore even the small initial particles can have large Stokes numbers causing them to drift already from the beginning on. This causes a visible particle wave in the simulation. By setting this parameter to `False`, these drifting particles will be removed.\n",
    "\n",
    "* erosionMassRatio\n",
    "\n",
    "If the mass ratio of colliding particles is below this ratio, both particles fully fragment, default: 10  \n",
    "In the standard model three things can happen when particles collide: they can stick together forming a larger particle, they can both fully fragment, or the smaller collision partner can fully fragment, chipping off some mass of the larger collision partner. The latter is called erosion. This parameter defines the threshold between full fragmentation and erosion.\n",
    "\n",
    "* d2gRatio\n",
    "\n",
    "Initial dust-to-gas ratio, default: $10^{-2}$\n",
    "\n",
    "* distExp\n",
    "\n",
    "Inital size distribution of particles, default: -7/2  \n",
    "The particles will initially have a size distribution of $n\\left(a\\right) \\propto a^\\mathrm{distExp}$ up to a maximum particle size of `Simulation.ini.dust.aIniMax`. The standard model uses the so-called MRN distribution of interstellar grains as initial condition. See [Mathis et al. (1977)](https://doi.org/10.1086/155591).\n",
    "\n",
    "* excavatedMass\n",
    "\n",
    "Excavated mass from larger particle in units of smaller particle mass, default: 1  \n",
    "In a erosive collision event the smaller particle will chip off mass from the larger particle. This parameter determines how much mass will be chipped off.\n",
    "\n",
    "* fragmentDistribution\n",
    "\n",
    "mass distribution of fragments, default: -11/6  \n",
    "Whenever a particle collision produces fragments the fragments will have a mass distribution of $n \\left(m\\right) \\mathrm{d}m \\propto m^\\mathrm{fragmentDistribution} \\mathrm{d}m$. The value used by the standard model is taken from [Dohnanyi (1969)](https://doi.org/10.1029/JB074i010p02531).\n",
    "\n",
    "* rhoMonomer\n",
    "\n",
    "Monomer bulk mass density, default: 1.67 g/cm³  \n",
    "In the standard model all particles will have a filling factor of unity and share therefore this bulk mass density.\n",
    "\n",
    "* vFrag\n",
    "\n",
    "Fragmentation velocity, default 1 m/s.  \n",
    "Particle collisions with a collision velocity that exceeds the fragmentation velocity will result in a fragmenting collision. Either full fragmentation or erosion depending on the mass ratio of the collision partners. Collisions below the fragmentation velocity lead to sticking."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Changing the Initial Conditions\n",
    "\n",
    "In this example we want to run a simulation with a more massive disk mass. We can use the constants module of `DustPy`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-30T11:25:19.512861Z",
     "iopub.status.busy": "2023-11-30T11:25:19.512241Z",
     "iopub.status.idle": "2023-11-30T11:25:19.517786Z",
     "shell.execute_reply": "2023-11-30T11:25:19.516630Z"
    }
   },
   "outputs": [],
   "source": [
    "from dustpy import constants as c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-30T11:25:19.522545Z",
     "iopub.status.busy": "2023-11-30T11:25:19.521927Z",
     "iopub.status.idle": "2023-11-30T11:25:19.527680Z",
     "shell.execute_reply": "2023-11-30T11:25:19.526577Z"
    }
   },
   "outputs": [],
   "source": [
    "sim.ini.gas.Mdisk = 0.1 * c.M_sun"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can now initialize the simulation as described in the previous section."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-30T11:25:19.533381Z",
     "iopub.status.busy": "2023-11-30T11:25:19.532755Z",
     "iopub.status.idle": "2023-11-30T11:25:19.863792Z",
     "shell.execute_reply": "2023-11-30T11:25:19.862964Z"
    }
   },
   "outputs": [],
   "source": [
    "sim.initialize()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Changing the Snapshots\n",
    "\n",
    "The standard model runs for 100,000 years and starts writing data files at 1,000 years with 10 files per time decade. In this example we only want to run the simulation for 10,000 years with only 5 snapshots per decade. This can easily be set by modifying `Simulation.t.snapshots`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-30T11:25:19.868819Z",
     "iopub.status.busy": "2023-11-30T11:25:19.868635Z",
     "iopub.status.idle": "2023-11-30T11:25:19.872217Z",
     "shell.execute_reply": "2023-11-30T11:25:19.871488Z"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-30T11:25:19.876652Z",
     "iopub.status.busy": "2023-11-30T11:25:19.876437Z",
     "iopub.status.idle": "2023-11-30T11:25:19.880455Z",
     "shell.execute_reply": "2023-11-30T11:25:19.879673Z"
    }
   },
   "outputs": [],
   "source": [
    "sim.t.snapshots = np.logspace(3, 4, num=6, base=10) * c.year"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Changing the Output Directory\n",
    "\n",
    "By default `DustPy` will protect already existing data files. If we ran the simulation now, an error would be raised, because we have already existing data files in the output directory from the previous chapter.\n",
    "\n",
    "We could either set `Simulation.writer.overwrite` to `True` to overwrite our existing data files or we could change the name of the output directory."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-30T11:25:19.884447Z",
     "iopub.status.busy": "2023-11-30T11:25:19.884238Z",
     "iopub.status.idle": "2023-11-30T11:25:19.887957Z",
     "shell.execute_reply": "2023-11-30T11:25:19.887102Z"
    }
   },
   "outputs": [],
   "source": [
    "sim.writer.datadir = \"2_data\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The simulation is now ready to go."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-30T11:25:19.892152Z",
     "iopub.status.busy": "2023-11-30T11:25:19.891847Z",
     "iopub.status.idle": "2023-11-30T11:30:12.390437Z",
     "shell.execute_reply": "2023-11-30T11:30:12.389448Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "DustPy v1.0.5\n",
      "\n",
      "Documentation: https://stammler.github.io/dustpy/\n",
      "PyPI:          https://pypi.org/project/dustpy/\n",
      "GitHub:        https://github.com/stammler/dustpy/\n",
      "\u001b[94m\n",
      "Please cite Stammler & Birnstiel (2022).\u001b[0m\n",
      "\n",
      "\u001b[93mChecking for mass conservation...\n",
      "\u001b[0m\n",
      "\u001b[93m    - Sticking:\u001b[0m\n",
      "\u001b[0m        max. rel. error: \u001b[92m 2.75e-14\u001b[0m\n",
      "        for particle collision\n",
      "            m[114] =  1.93e+04 g    with\n",
      "            m[116] =  3.73e+04 g\u001b[0m\n",
      "\u001b[93m    - Full fragmentation:\u001b[0m\n",
      "\u001b[0m        max. rel. error: \u001b[92m 5.55e-16\u001b[0m\n",
      "        for particle collision\n",
      "            m[55] =  7.20e-05 g    with\n",
      "            m[55] =  7.20e-05 g\u001b[0m\n",
      "\u001b[93m    - Erosion:\u001b[0m\n",
      "\u001b[0m        max. rel. error: \u001b[92m 1.78e-15\u001b[0m\n",
      "        for particle collision\n",
      "            m[110] =  5.18e+03 g    with\n",
      "            m[118] =  7.20e+04 g\n",
      "\u001b[0m\n",
      "Creating data directory '2_data'.\n",
      "Writing file \u001b[94m2_data/data0000.hdf5\u001b[0m\n",
      "Writing dump file \u001b[94m2_data/frame.dmp\u001b[0m\n",
      "Writing file \u001b[94m2_data/data0001.hdf5\u001b[0m\n",
      "Writing dump file \u001b[94m2_data/frame.dmp\u001b[0m\n",
      "Writing file \u001b[94m2_data/data0002.hdf5\u001b[0m\n",
      "Writing dump file \u001b[94m2_data/frame.dmp\u001b[0m\n",
      "Writing file \u001b[94m2_data/data0003.hdf5\u001b[0m\n",
      "Writing dump file \u001b[94m2_data/frame.dmp\u001b[0m\n",
      "Writing file \u001b[94m2_data/data0004.hdf5\u001b[0m\n",
      "Writing dump file \u001b[94m2_data/frame.dmp\u001b[0m\n",
      "Writing file \u001b[94m2_data/data0005.hdf5\u001b[0m\n",
      "Writing dump file \u001b[94m2_data/frame.dmp\u001b[0m\n",
      "Writing file \u001b[94m2_data/data0006.hdf5\u001b[0m\n",
      "Writing dump file \u001b[94m2_data/frame.dmp\u001b[0m\n",
      "Execution time: \u001b[94m0:04:52\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "sim.run()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The simulation has now run for 10,000 years"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-30T11:30:12.397645Z",
     "iopub.status.busy": "2023-11-30T11:30:12.397376Z",
     "iopub.status.idle": "2023-11-30T11:30:12.404299Z",
     "shell.execute_reply": "2023-11-30T11:30:12.403512Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10000.0"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sim.t / c.year"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "and we can have a look at the current state."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-30T11:30:12.409937Z",
     "iopub.status.busy": "2023-11-30T11:30:12.409653Z",
     "iopub.status.idle": "2023-11-30T11:30:12.414063Z",
     "shell.execute_reply": "2023-11-30T11:30:12.413197Z"
    }
   },
   "outputs": [],
   "source": [
    "from dustpy import plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-30T11:30:12.418809Z",
     "iopub.status.busy": "2023-11-30T11:30:12.418420Z",
     "iopub.status.idle": "2023-11-30T11:30:13.755195Z",
     "shell.execute_reply": "2023-11-30T11:30:13.753995Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1575x648.949 with 7 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot.panel(sim)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When calling `Simulation.run()`, `DustPy` will perform a small mass conservation check, by going through all possible collisions and calculating their relative mass error. The limitation here is machine precision. Everything smaller than $10^{-13}$ is still acceptable. If you created your own collision model, that is not compatible with the default sticking-erosion-fragmentation model, you can either ignore the output, or you can overwrite the `Simulation.checkmassconservation()` function that is called by default when calling `Simulation.run()`.\n",
    "\n",
    "See a later chapter for details on coagulation."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}